Giter Club home page Giter Club logo

parca-agent's Introduction

Build Apache 2 License

Parca Agent

Parca Agent is an always-on sampling profiler that uses eBPF to capture raw profiling data with very low overhead. It observes user-space and kernel-space stacktraces 100 times per second and builds pprof formatted profiles from the extracted data. Read more details in the design documentation.

The collected data can be viewed locally via HTTP endpoints and then be configured to be sent to a Parca server to be queried and analyzed over time.

It discovers targets through:

  • Kubernetes: Discovering all the containers on the node the Parca agent is running on. (On by default, but can be disabled using --kubernetes=false)
  • systemd: A list of systemd units to be profiled on a node can be configured for the Parca agent to pick up. (Use the --systemd-units flag to list the units to profile, eg. --systemd-units=docker.service to profile the docker daemon)

Requirements

  • Linux Kernel version 4.18+
  • A source of targets to discover from: Kubernetes or systemd.

Quickstart

See the Kubernetes Getting Started.

Supported Profiles

Profiles available for compiled languages (eg. C, C++, Go, Rust):

  • CPU
  • Soon: Network usage, Allocations

The following types of profiles require explicit instrumentation:

  • Runtime specific information such as Goroutines

Debugging

Web UI

The HTTP endpoints can be used to inspect the active profilers, by visiting port 7071 of the process (the host-port that the agent binds to can be configured using the --http-address flag).

On a minikube cluster that might look like the following:

Active Profilers

And by clicking "Show Profile" in one of the rows, the currently collected profile will be rendered once the collection finishes (this can take up to 10 seconds).

Profile View

A raw profile can also be downloaded here by clicking "Download Pprof". Note that in the case of native stack traces such as produced from compiled language like C, C++, Go, Rust, etc. are not symbolized and if this pprof profile is analyzed using the standard pprof tooling the symbols will need to be available to the tooling.

Logging

To debug potential errors, enable debug logging using --log-level=debug.

Configuration

Flags:

Usage: parca-agent --node=STRING

Flags:
  -h, --help                    Show context-sensitive help.
      --log-level="info"        Log level.
      --http-address=":7071"    Address to bind HTTP server to.
      --node=STRING             Name node the process is running on. If on
                                Kubernetes, this must match the Kubernetes node
                                name.
      --external-label=KEY=VALUE;...
                                Label(s) to attach to all profiles.
      --store-address=STRING    gRPC address to send profiles and symbols to.
      --bearer-token=STRING     Bearer token to authenticate with store.
      --bearer-token-file=STRING
                                File to read bearer token from to authenticate
                                with store.
      --insecure                Send gRPC requests via plaintext instead of TLS.
      --insecure-skip-verify    Skip TLS certificate verification.
      --sampling-ratio=1.0      Sampling ratio to control how many of the
                                discovered targets to profile. Defaults to 1.0,
                                which is all.
      --kubernetes              Discover containers running on this node to
                                profile automatically.
      --pod-label-selector=STRING
                                Label selector to control which Kubernetes Pods
                                to select.
      --systemd-units=SYSTEMD-UNITS,...
                                systemd units to profile on this node.
      --temp-dir="/tmp"         Temporary directory path to use for object
                                files.
      --socket-path=STRING      The filesystem path to the container runtimes
                                socket. Leave this empty to use the defaults.

systemd

To discover systemd units, the names must be passed to the agent. For example, to profile the docker daemon pass --systemd-units=docker.service.

Sampling

Sampling Ratio

To sample all targets, either to save resources on storage or reduce overhead, use the --sampling-ratio flag. For example, to profile only 50% of the discovered targets use --sampling-ratio=0.5.

Kubernetes label selector

To further sample targets on Kubernetes use the --pod-label-selector= flag. For example to only profile Pods with the app.kubernetes.io/name=my-web-app label, use --pod-label-selector=app.kubernetes.io/name=my-web-app.

Roadmap

  • Additional language support for just-in-time (JIT) compilers, and dynamic languages (non-exhaustive list):
    • Ruby
    • Node.js
    • Python
    • JVM
  • Additional types of profiles:
    • Memory allocations
    • Network usage

Security

Parca Agent requires to be run as root user (or CAP_SYS_ADMIN). Various security precautions have been taken to protect users running Parca Agent. See details in Security Considerations.

To report a security vulnerability see this guide.

Contributing

Check out our Contributing Guide to get started!

License

Apache 2

Credits

Thanks to:

  • Aqua Security for creating libbpfgo (cgo bindings for libbpf), while we contributed several features to it, they have made it spectacularly easy for us to contribute and it has been a great collaboration. Their use of libbpf in tracee has also been a helpful resource.
  • Kinvolk for creating Inspektor Gadget some parts of this project were inspired by parts of it.

parca-agent's People

Contributors

brancz avatar kakkoyun avatar dependabot[bot] avatar paulfantom avatar sylfrena avatar thorfour avatar metalmatze avatar arthursens avatar frezbo avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.